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Plasmid-dependent phages infect bacteria carrying conjugative plasmids by recognizing the plasmid-encoded pilus. Despite the high abundance of conjugative plasmids in diverse environments, plasmid-dependent phages have not been widely studied. Since conjugative plasmids often carry antimicrobial resistance genes (ARGs), interfering with conjugation could reduce the spread of ARGs and avoid the appearance of multiresistant superbugs. Our aim was to isolate and characterize plasmid-dependent phages able to infect bacteria carrying diverse conjugative plasmids belonging to the most common plasmid families among Gram-negative pathogens. We isolated two lytic phages from wastewater using an avirulent strain of Salmonella enterica carrying the conjugative IncN plasmid pKM101. Both phages, named Lu221 and Hi226, are novel dsDNA viruses within the class Caudoviricetes with genomes of approximately 76 kb. They showed broad host range infecting Escherichia coli, S. enterica, Kluyvera sp., and Enterobacter sp. carrying conjugative plasmids. They recognize plasmid-encoded receptors from 12 out of 15 tested plasmids, all of them carrying resistance determinants. Phages Lu221 and Hi226 could have the potential to help combat the antimicrobial resistance crisis by reducing ARGs present in conjugative plasmids.

IMPORTANCE: This work was undertaken because plasmid-dependent phages can reduce the prevalence of conjugative plasmids and can be leveraged to prevent the acquisition and dissemination of ARGs by bacteria. The two novel phages described in this study, Lu221 and Hi226, can infect Escherichia coli, Salmonella enterica, Kluyvera sp. and Enterobacter sp. carrying conjugative plasmids. This was verified with plasmids carrying resistance determinants and belonging to the most common plasmid families among Gram-negative pathogens. Therefore, the newly isolated phages could have the potential to help control the spread of ARGs and thus help combat the antimicrobial resistance crisis.

Microbes are commonly found in aggregated form, where a community of various microbial species fill a variety of ecological niches. They play an essential role in global nutrient cycles, human and animal health, and in numerous industrial applications. Microbial aggregates, in many cases referred to as bio-films, have a dynamic life cycle. The cycle starts when planktonic cells start attaching to a surface or other cells. In this so called reversible attachment phase microbial surface properties such as the hydrophobicity of the cell play a key role. After this the nascent biofilm enters the irreversible attachment phase, more cells continue to be embedded in the growing aggregate, and phenotypic changes associated with microbial life in a biofilm, including the production of large quantities of Extracellular Polymeric Substances (EPS), start to occur. As the aggregate grows, spatial structures such as microcolonies and stratification start to emerge. Mature biofilms may get into a final phase in which EPS degradation occurs and cells disperse into the environment. The spatial and community structure of a microbial aggregate result from a combination of physical processes such as matter transport and mechanical stresses acting upon the microbial aggregate, and the individual traits and behavior of the microbes embedded in the aggregate. Due to the complexity of multi-species microbial aggregates and our limited ability to observe the dynamic development of internal structures and biochemical conditions in microbial aggregates, modeling approaches have played a substantial role in biofilm research. The first mathematical and computational biofilm models, developed over half a century ago, clarified how, through diffusion limitation, chemical gradients form within microbial aggregates that can in turn, lead to the stratification of microbial species in the aggregate. Later, Individual-based Models (IbM) showed how individual traits and variability can affect

Microbial communities are found in all habitable environments and often occur in assemblages with self-organized spatial structures developing over time. This complexity can only be understood, predicted, and managed by combining experiments with mathematical modeling. Individual-based models are particularly suited if individual heterogeneity, local interactions, and adaptive behavior are of interest. Here we present the completely overhauled software platform, the individual-based Dynamics of Microbial Communities Simulator, iDynoMiCS 2.0, which enables researchers to specify a range of different models without having to program. Key new features and improvements are: (1) Substantially enhanced ease of use (graphical user interface, editor for model specification, unit conversions, data analysis and visualization and more). (2) Increased performance and scalability enabling simulations of up to 10 million agents in 3D biofilms. (3) Kinetics can be specified with any arithmetic function. (4) Agent properties can be assembled from orthogonal modules for pick and mix flexibility. (5) Force-based mechanical interaction framework enabling attractive forces and non-spherical agent morphologies as an alternative to the shoving algorithm. The new iDynoMiCS 2.0 has undergone intensive testing, from unit tests to a suite of increasingly complex numerical tests and the standard Benchmark 3 based on nitrifying biofilms. A second test case was based on the "biofilms promote altruism" study previously implemented in BacSim because competition outcomes are highly sensitive to the developing spatial structures due to positive feedback between cooperative individuals. We extended this case study by adding morphology to find that (i) filamentous bacteria outcompete spherical bacteria regardless of growth strategy and (ii) non-cooperating filaments outcompete cooperating filaments because filaments can escape the stronger competition between themselves. In conclusion, the new substa